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@ -707,12 +707,11 @@ class Text2SemanticDecoder(nn.Module):
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if idx == 0:
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if idx == 0:
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attn_mask = F.pad(attn_mask[:, :, -1].unsqueeze(-2), (0, 1), value=False)
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attn_mask = F.pad(attn_mask[:, :, -1].unsqueeze(-2), (0, 1), value=False)
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logits = logits[:, :-1]
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else:
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else:
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attn_mask = F.pad(attn_mask, (0, 1), value=False)
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attn_mask = F.pad(attn_mask, (0, 1), value=False)
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if idx < 11: ###至少预测出10个token不然不给停止(0.4s)
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if idx < 11: ###至少预测出10个token不然不给停止(0.4s)
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logits = logits[:, :-1]
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logits = logits[:, :-1]
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samples = sample(
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samples = sample(
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logits, y, top_k=top_k, top_p=top_p, repetition_penalty=repetition_penalty, temperature=temperature
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logits, y, top_k=top_k, top_p=top_p, repetition_penalty=repetition_penalty, temperature=temperature
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@ -347,7 +347,7 @@ Use v4 from v1/v2/v3 environment:
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2. Clone the latest codes from github.
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2. Clone the latest codes from github.
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3. Download v4 pretrained models (gsv-v4-pretrained/s2v4.ckpt, and gsv-v4-pretrained/vocoder.pth) from [huggingface](https://huggingface.co/lj1995/GPT-SoVITS/tree/main) and put them into `GPT_SoVITS/pretrained_models`.
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3. Download v4 pretrained models (gsv-v4-pretrained/s2v4.pth, and gsv-v4-pretrained/vocoder.pth) from [huggingface](https://huggingface.co/lj1995/GPT-SoVITS/tree/main) and put them into `GPT_SoVITS/pretrained_models`.
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## V2Pro Release Notes
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## V2Pro Release Notes
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